The Signal and the Noise
Why So Many Predictions Fail - But Some Don't
Ratings70
Average rating4
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Why So Many Predictions Fail - But Some Don't
Ratings70
Average rating4
Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger—all by the time he was thirty. The New York Times now publishes FiveThirtyEight.com, where Silver is one of the nation’s most influential political forecasters.
Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the “prediction paradox”: The more humility we have about our ability to make predictions, the more successful we can be in planning for the future.
In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good—or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary—and dangerous—science.
Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise.
With everything from the health of the global economy to our ability to fight terrorism dependent on the quality of our predictions, Nate Silver’s insights are an essential read.
Reviews with the most likes.
It goes without saying that “popular statistics” book is mostly an oxymoron. On the one hand, statistics is largely a very dry field. On the other hand, those of us who do understand statistics (and even freaks, like my husband, who enjoy statistics), find any attempt at popular statistics largely too elementary to be interesting. Nate Silver doesn't just walk the fine line in the middle, he eliminates it and writes a completely novel statistic book that is appealing to both the mathematician and the math hater: this book fascinates.
Nate Silver focuses on the forecasting in areas that are difficult to predict: weather, climate, earthquakes, poker, politics, chess and sports. Each of these areas is individually interesting – I had never spent much time considering online poker, for instance, and the chapter focusing on poker is not just mathematically-focused, but also an expose on the world of online poker and the life and times (or at least the two year subset thereof) of Silver's 6-figure gambling career. In addition, his overall thesis, which seems to be that we should use Bayesian analysis to think probabilistically about the world and continually evaluate our probabilities both builds naturally and has far-reaching applications.
I feel like I have spent years of my life trying to explain to medical students (and more advanced physicians who should really know better) why every time a paper is published with a p<0.05 we can't totally disregard all prior medical knowledge and dive after the new information. Silver's easy explanation of Bayes' theorem nicely summarizes why this is true - that alone should make this a must-read for anyone in an academic field.
I am a schedule reader, which is usually nice because the hype has often died way down before I get to something and I can read it on its own terms. But then we get situations like this one, where the air has gone pretty spectacularly out of Nate Silver's balloon in the time since I bought the book. When his star was burning bright in the wake of the 2012 election though, everyone wanted to know how he looked at data to make his predictions. The insights he offers aren't especially unique or profound: generally, people are not as good as they could be at making predictions because of various biases, particularly confirmation bias, and also the tendency to not learn from mistakes and adjust models to take new data into account. He then sets about presenting various examples of prediction and its failures: political talking heads, weather, the 2008 recession, earthquakes, the trajectories of baseball players' careers, before spending the second half of the book writing a love letter to Baynesian statistics. It's much too long, about 450 pages before footnotes, and the prose style is fairly dry so it's very hard to stay interested. A big miss for me.
